Zhan and co-workers developed a new method that will allow the intricate processes underlying lasso peptide biosynthesis to be interrogated for the first time. Using the tools of artificial intelligence (AI) and computational modeling, they identified critical information that could be used in the discovery of innovative drugs.
Unraveling the Lasso Knot
Lasso peptides are an atypical family of ribosomally synthesized and post-translationally modified peptides (RiPPs) made by bacteria. Not only are these molecules flipping cool looking with lasso-like structure that allows them to be as stable and sturdy as they are, but they can also fend off surprises from the environment.
In the more than three decades since then, it is indeed astounding to know how scientists still mull over how these peptides are synthesized. A key peptidase and cyclase enzyme pair operate in concert, chopping up a long precursor peptide to form the characteristic knotted topology. However, in order to truly harness the power of this process, we must first understand the precise mechanisms by which its folding occurs.
In this study, researchers have tackled the issue head-on by using artificial intelligence to reveal the secrets of the lasso peptide cyclase. Using state-of-the-art computational models (e.g., AlphaFold and RODEO) they predicted the 3D structure of the FusC cyclase and identified key amino acid residues that interact with the peptide substrate. The new methodology is a significant step forward in terms of the insight into biophysical interactions that dictate lasso knot formation remains unrivaled.
Engineering Diversity into Lasso Peptides
According to the researchers, discovering the underlying mechanisms is not only important. Here, they have shown how this knowledge can be used to enable the engineering of new and diverse lasso peptides, which may broaden the therapeutic applicability of these extraordinary molecules.
Using the information they gleaned from their benchtop studies, the team found a mutant variant of FusC cyclase capable of folding new lasso peptides based on computational findings. An accomplishment that says not only much about their computational model, but enormities about what could be the generation of lasso peptide-based therapeutics.
This study was also part of a collaboration with the biotechnology company Lassogen, which aimed to demonstrate the applications of this research. In addition, they engineered another cyclase (McjC) to efficiently synthesize an inhibitor of integrin closely linked with cancer; this shows the flexibility of their strategy. The discovery illustrates the enormous potential of lasso peptides as a goldmine to be exploited for drug discovery and development.
Conclusion
The new methodology, presented in this study is an exquisite example of using frontier research as a source for transformation to improve drug discovery by deploying inter-disciplinary group and advanced in silico tools. Underpinning the approach that we can develop with natural lasso peptides to fight a diverse array of diseases from cancer to viral infections, the researchers have cracked open the complex machinery underpinning their formation. This study is bound to be the foundation on which future novel treatments will advance, as the field progresses.
